AIMC Topic: Female

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Evaluation of Vertical Ground Reaction Forces Pattern Visualization in Neurodegenerative Diseases Identification Using Deep Learning and Recurrence Plot Image Feature Extraction.

Sensors (Basel, Switzerland)
To diagnose neurodegenerative diseases (NDDs), physicians have been clinically evaluating symptoms. However, these symptoms are not very dependable-particularly in the early stages of the diseases. This study has therefore proposed a novel classifica...

Integration of an interpretable machine learning algorithm to identify early life risk factors of childhood obesity among preterm infants: a prospective birth cohort.

BMC medicine
BACKGROUND: The early life risk factors of childhood obesity among preterm infants are unclear and little is known about the influence of the feeding practices. We aimed to identify early life risk factors for childhood overweight/obesity among prete...

Feasibility of a 5G-Based Robot-Assisted Remote Ultrasound System for Cardiopulmonary Assessment of Patients With Coronavirus Disease 2019.

Chest
BACKGROUND: Traditional methods for cardiopulmonary assessment of patients with coronavirus disease 2019 (COVID-19) pose risks to both patients and examiners. This necessitates a remote examination of such patients without sacrificing information qua...

Development and Validation of Forecasting Next Reported Seizure Using e-Diaries.

Annals of neurology
OBJECTIVE: There are no validated methods for predicting the timing of seizures. Using machine learning, we sought to forecast 24-hour risk of self-reported seizure from e-diaries.

Time-resolved neurotransmitter detection in mouse brain tissue using an artificial intelligence-nanogap.

Scientific reports
The analysis of neurotransmitters in the brain helps to understand brain functions and diagnose Parkinson's disease. Pharmacological inhibition experiments, electrophysiological measurement of action potentials, and mass analysers have been applied f...

Fully bayesian longitudinal unsupervised learning for the assessment and visualization of AD heterogeneity and progression.

Aging
Tau pathology and brain atrophy are the closest correlate of cognitive decline in Alzheimer's disease (AD). Understanding heterogeneity and longitudinal progression of atrophy during the disease course will play a key role in understanding AD pathoge...

Deep neural network analyses of spirometry for structural phenotyping of chronic obstructive pulmonary disease.

JCI insight
BACKGROUNDCurrently recommended traditional spirometry outputs do not reflect the relative contributions of emphysema and airway disease to airflow obstruction. We hypothesized that machine-learning algorithms can be trained on spirometry data to ide...

Development of machine learning models to prognosticate chronic shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage.

Acta neurochirurgica
BACKGROUND: Shunt-dependent hydrocephalus significantly complicates subarachnoid hemorrhage (SAH), and reliable prognosis methods have been sought in recent years to reduce morbidity and costs associated with delayed treatment or neglected onset. Mac...

Diagnostic performance of fetal intelligent navigation echocardiography (FINE) in fetuses with double-outlet right ventricle (DORV).

The international journal of cardiovascular imaging
The main objective of this study was to investigate the diagnostic performance of FINE in generating and displaying 3 specific abnormal fetal echocardiography views such as left ventricular outflow tract (LVOT) view, right ventricular outflow tract (...

Identifying Fatal Head Injuries on Postmortem Computed Tomography Using Convolutional Neural Network/Deep Learning: A Feasibility Study.

Journal of forensic sciences
Postmortem computed tomography (PMCT) is a relatively recent advancement in forensic pathology practice that has been increasingly used as an ancillary investigation and screening tool. One area of clinical CT imaging that has garnered a lot of resea...